The binary joint transform correlator (BJTC) can easily be applied to fingerprint identification or recognition; see K. H. Fielding, J. L. Horner, and C. K. Makekau, xe2x80x9cOptical fingerprint identification by binary joint transform correlation,xe2x80x9d Opt. Eng. 30, 1958-1961, (1991); B. Javidi, and J. L. Horner., xe2x80x9cOptical pattern recognition for validation and security verification,xe2x80x9d Opt. Eng. 33, 1752-1756, (1994).
Since fingerprint recognition involves comparison of a pair of complicated images, it is an ideal application for optical correlators. While it is not clear that optical processing will ever yield a sizable speed increase over digital parallel processing, using a small digital computer with an optical coprocessor clearly has the potential for reduced size, weight, and power consumption over a digital multiprocessor computer with comparable performance for this application. To assess performance of a recognition system, the ability to discriminate matched prints from unmatched prints should be studied from a statistical viewpoint: see T. J. Grycewicz, xe2x80x9cFingerprint recognition using the binary nonlinear joint transform correlator,xe2x80x9d Optoelectronic Devices and Systems for Processing, Bahram Javidi and Kristina M. Johnson, ed., Critical Reviews of Optical Science and Technology, Vol. CR65, SPIE Press c. 1996.
Matched prints, referred to herein, are images of the same finger taken at different times, and unmatched prints are images of different fingers. To assure a low probability of false alarm and a low probability of false pass, it is necessary that the largest output peaks for unmatched prints be smaller than the smallest peaks seen for matched prints, in the presence of reasonable distortions from rotation, cuts, abrasions, stretching of the skin, or dirt. The performance metric used here was the probability of passing a false print under the constraint of a constant false alarm rate (CFAR).
It would be desirable to improve the performance of a single spatial light modulator (SLM) BJTC fingerprint correlator; see F. T. S. Yu, et al., xe2x80x9cAdaptive real-time pattern recognition using a liquid crystal TV based joint transform correlatorxe2x80x9d, Appl. Opt. 26, 1370 (1984).
A number of techniques have been presented for improving binary joint transform correlator (BJTC) performance, and have been shown to improve performance of fingerprint recognition systems. Frame subtraction is one; see T. J. Grycewicz and B. Javidi, xe2x80x9cExperimental comparison of binary joint transform correlators used for fingerprint identification,xe2x80x9d Opt. Eng. 35, 2519-2525 (1996); and processing of a partial Fourier plane is another; see T. J. Grycewicz, xe2x80x9cFingerprint recognition using the binary nonlinear joint transform correlator,xe2x80x9d Optoelectronic Devices and Systems for Processing, Bahram Javidi and Kristina M. Johnson, ed., Critical Reviews of Optical Science and Technology, Vol. CR65. SPIE Press c. 1996.
These additional techniques can be utilized to further improve the performance of the BJTC fingerprint recognition system.
Noise in the Fourier plane of a BJTC is screened out by applying a binarization threshold which alternates between even and odd rows in the Fourier plane. Use of such alternating threshold reduces the effect of low amplitude Fourier plane signals on the output, and improves the system capability to discriminate between weak correlations and noise by a factor of greater than three. To counter output amplitude drift in the BJTC system, the output peak heights are normalized, to improve performance by a factor of almost three. When the two techniques are used together, a combined dramatic performance improvement to be described is attained.